Tensor Robust Principal Component Analysis with Low-Rank Weight Constraints for Sample Clustering.
Yu-Ying ZhaoMao-Li WangJuan WangShasha YuanJin-Xing LiuXiang-Zhen KongPublished in: BIBM (2020)
Keyphrases
- robust principal component analysis
- low rank
- high order
- trace norm
- high dimensional data
- missing data
- convex optimization
- low rank matrix
- rank minimization
- matrix factorization
- linear combination
- matrix completion
- singular value decomposition
- low rank and sparse
- clustering method
- semi supervised
- kernel matrix
- clustering algorithm
- k means
- minimization problems
- dimensionality reduction
- higher order
- data clustering
- singular values
- data matrix
- foreground detection
- data points
- nuclear norm
- affinity matrix
- feature selection
- small number
- least squares